code: def gram_matrix(feature_maps):
      """Computes the Gram matrix for a set of feature maps."""
      batch_size, height, width, channels = tf.unstack(
          tf.shape(feature_maps)
      )
      denominator = tf.to_float(height * width)
      feature_maps = tf.reshape(
          feature_maps, tf.stack([batch_size, height * width, channels])
      )
      matrix = tf.matmul(feature_maps, feature_maps, adjoint_a=True)
      return matrix / denominator
  
file_path: magenta/magenta/models/image_stylization/learning.py
imports: from magenta.models.image_stylization import vgg
  import numpy
  import tensorflow.compat.v1
  import tf_slim
label_desc: Use image node_id 6 for calling a global function with example usage: gram_matrix(feature_maps) and returns: unknown